Missing Data in Patient-Reported Outcomes Research: Utilizing Multiple Imputation to Address an Unavoidable Problem.

ABSTRACT:

Background

Patient-reported outcomes (PROs) have become a focus in postoperative surgical care. Unfortunately, studies using PROs can be subject to missing data, which may lead to biases or inaccurate conclusions. Multiple imputation (MI) is a statistical method for addressing missing data in clinical research. The aim of this study was to explore MI as a way to address missing data in PRO research.

Methods

A working example of MI using real-world data was performed using the BREAST-Q PRO measure in postmastectomy reconstruction. A retrospective review of immediate tissue expander breast reconstruction patients in 2019 was conducted to compare BREAST-Q physical well-being of the chest scores between prepectoral and subpectoral cohorts at 2 weeks postoperatively. The observed

SUBMITTER: Haglich K 

PROVIDER: S-EPMC11151661 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature